I’m an array language novice but my favorite one so far is BQN. Much better documented than K derivatives. Not sure you could characterize any array language as having a “healthy userbase” though.
For any other array language novices, I've experimented with K and J but had the best experience so far with BQN. It is a bit on the Lispy side like K but much better documented, and I thought the APL-esque symbolic alphabet was mnemonically helpful enough while reading code to justify learning an editor keyboard integration. (Plus it's fun.)
I respect the forecasting abilities of the people involved, but I have seen that report described as "astonishingly accurate" a few times and I'm not sure that's true. The narrative format lends itself somewhat to generous interpretation and it's directionally correct in a way that is reasonably impressive from 2021 (e.g. the diplomacy prediction, the prediction that compute costs could be dramatically reduced, some things gesturing towards reasoning/chain of thought) but many of the concrete predictions don't seem correct to me at all, and in general I'm not sure it captured the spiky nature of LLM competence.
I'm also struck by the extent to which the first series from 2021-2026 feels like a linear extrapolation while the second one feels like an exponential one, and I don't see an obvious justification for this.
Plenty of people are ragging (justifiably) on Clean Code, but I really admire by contrast Ousterhout's commitment to balanced principles and in particular learning from non-trivial examples. Philosophy of Software Design is a great and thought-provoking read.